Visualizing Bicycle Data

May 15, 2016

A question transportation professionals often have is how can we communicate all this information and data we have in a visually appealing and interesting way.

Divvy BikeShare in Chicago publically released 2013 ridership data, and hosted a competition to encourage people to analyze this data and present it in cool and innovative ways. The question was, how does this relatively recent transportation solution (BikeShare Divvy in Chicago was introduced that same year - 2013) affect the way people travel?

This submission is a simple yet ingenious heat map aggregating bike trips throughout the city to answer the question: how are people using the BikeShare system? The map divides the city into regions according to station locations and determines which are the most common stations people are traveling to. A tightly grouped spread means that most commuters are using that Divvy station as a “last mile” transportation solution, bridging the gap between public transportation and their destination, while larger spreads can be seen as bike trips replacing public transit trips. To me this really shows that BikeShare should be considered as a complementary system to public transit and an affordable method to move people where they want to go.